Training Day
NoSQL matters Training Day 21-11-2014
NoSQL matters training day will give you an opportunity to dive deeply into the secrets of selected databases. Get the information from first hand and enjoy familiar atmosphere in the small groups. Each training slot will last 4h. You can choose a training session in the morning and one in the afternoon. Please ensure to provide your own laptop.
We will offer soft drinks and coffee during the day and a warm lunch will be served.
In the meantime – have a glimpse into what’s coming! The tickets sale is on!
Time | Aula 01 | Aula 02 | Aula 04 |
8:30 – 8:55 | Registration | ||
9:00 – 13:00 | Training is Sold Out Data Modelling in a NoSQL world Max Neunhöffer |
Training is Sold Out Time series on HBase Richard Shaw |
Training is Sold Out Introduction to high performance graph data management with Sparksee Arnau Prat & Joan Guisado |
13:00 – 13:45 | Lunch | ||
13:45 – 17:45 | Training is Sold Out Highly available Redis with Redis Sentinel Salvatore Sanfilippo |
Training is Sold Out Graph querying at large scale Dr. Frank Celler |
Training is Sold Out Introduction to Apache Cassandra, CQL and Data Modelling Duy Hai DOAN |
Many popular graph databases are optimized to run on a single machine, using efficient traversals to query the stored graphs. This boosts performance of algorithms originating at a single vertex and iterating through the graph.
However, graphs are getting bigger and traversals are poorly performing if they hit a large depth. If you need to distribute a large-scale graph to several machines, traversals won’t be the best choice in case of performance to process the graph. Therefore Google has released it’s Pregel framework offering an environment to query distributed graphs. In this training we will learn about the architecture and workflow of the Pregel framework. Furthermore we will learn how to write queries on a Pregel implementation. During these queries we will learn about the different mind-set required for Pregel queries and will learn some tricks and tweaks to avoid limitations introduced by the Pregel architecture.
The participants are not required to have any prior knowledge to the Pregel framework or to graph algorithms.
Participants are required to bring their own notebook with a new version of VirtualBox installed.
Trainer: Dr. Frank Celler
Level of the training: Beginner
Data Modelling in a NoSQL world
Learn about data modelling in a NoSQL environment in this half-day class.
Even though most NoSQL databases follow the “schema-free” data paradigma, what a database is really good at is determined by its underlying architecture and storage model.
It is therefore important to choose a matching data model to get the best out of the underlying database technology. Application requirements such as consistency demands also need to be considered.
During the half-day, attendees will get an overview of different data storage models available in NoSQL databases. There will also be hands-on examples and experiments using key/value, document, and graph data structures.
No prior knowledge of NoSQL databases is required. Some basic experience with relational databases (like MySQL) or data modelling will be helpful but is not essential. Participants will need to bring their own laptop (preferably Linux or MacOS). Installation instructions for the required software will be sent out prior to the class.
Trainer: Max Neunhöffer, Senior Developer, triAGENS GmbH
Level of the training: Intermediate
Time series data. It’s definitely come to prominance with the Internet of Things, and there may be more of it out there, but it’s still time series data which we’ve been handling in different ways for years. We’ll show you how to use HBase to ingest a time series data set in real time and query it, providing a real-time operational solution. We’ll also walk you through design decisions and some of the Hadoop components you can then leverage for greater insight.
Participants should bring a laptop with a browser and an SSH client.
Trainer: Richard Shaw, Solutions Architect, MapR Technologies
Level of the training: Beginner/ Intermediate
Introduction to Apache Cassandra, CQL and Data Modelling
DataStax provides a massively scalable enterprise NoSQL platform to run mission-critical business applications for some of the world’s most innovative and data-intensive enterprises, such household names Netflix and eBay. Powered by the open source Apache Cassandra™ database, DataStax delivers the world’s fasted and most scalable distributed database technology.This workshop session will take a look at Cassandra, covering CQL and Data Modelling with a chance for hands on activity (time permitting).
Topics covered:
Introduction to Cassandra
core concepts, availability, scalability, security + appropriate hardware + use cases for Cassandra + DataStax Enterprise
CQL and Data Modelling
Detailed overview of CQL + Data Modelling Approaches + Tools + Hands on Exercises
Native driver and protocol
An overview of the native driver and protocol + Tips and examples using the Java Driver
Cassandra 1.2, 2.0 and 2.1
A high level overview of the functionality and features in these versions
Hands-on workshop (time permitting)
Build a very simple Java application connecting to Cassandra
Trainer: Duy Hai DOAN, Technical Advocate, DataStax
Level of the training: Beginner/ Intermediate
Highly available Redis with Redis Sentinel
During the training section Salvatore will show what Redis Sentinel is, the algorithms it uses, how to mount a Redis high available environment using it, the way it interacts with client libraries during failover, and the different tradeoffs that can be made in the setup. A public example, specifically the Flickr Sentinel deployment, will be analyzed as an use case.
Participants are required to be familiar with Redis and with basic distributed systems concepts.
Trainer: Salvatore ‘antirez’ Sanfilippo, Open Source Developer, GoPivotal
Level of the training: Expert
Introduction to high performance graph data management with Sparksee
With the advent of the Data era, Graph Databases are emerging as a key technology for efficiently querying complexly structured data, such those found in the domains of social networks, gaming and fraud detection, to cite just a few of them.
In this session attendees will learn how to model and load data as a graph, and discover the full potential of graph databases and what can they offer compared to other traditional database paradigms. We will use Sparksee high-performance graph database, which is designed for efficiently query large graphs like those found in the real world.
Requirements: Attendees must bring their own laptops with Netbeans installed.
Trainer: Arnau Prat, Social Network Analysis Researcher, Sparsity & Joan Guisado, Search Engines Researcher, Sparsity
Level of the training: Beginner, no prior knowledge on graph databases is required to attend this session.